How to Download and Use DSpace 2017b with MATLAB
DSpace is an open source repository software package that allows users to capture, store, index, preserve, and distribute digital material, such as text, video, audio, and data. It is widely used as an institutional repository for research output, scholarly publications, library collections, and more.
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MATLAB is a high-level programming language and environment for numerical computation, visualization, and application development. It supports various domains and applications, such as engineering, science, education, finance, robotics, image processing, machine learning, and more.
Using DSpace with MATLAB can provide many benefits for researchers, engineers, educators, and students who want to create, share, and reuse models and data in a secure and reliable way. DSpace can help them manage their digital assets, collaborate with others, publish their results, and preserve their work for future use. MATLAB can help them develop, test, and deploy models using various tools and methods, such as Simulink, Stateflow, RTI Blocksets, Real-Time Testing, TargetLink, VEOS, etc.
In this article, we will show you how to download DSpace 2017b, the latest version of the software released in January 2018. We will also show you how to use DSpace 2017b with MATLAB to create, run, and test models using different tools and platforms. We will assume that you have some basic knowledge of DSpace and MATLAB concepts and features. If not, you can refer to the documentation and tutorials available on their websites.
How to Download DSpace 2017b
Before you download DSpace 2017b, you need to make sure that your system meets the minimum requirements and supports the platforms that you want to use. Here are some of the main system requirements for DSpace 2017b:
Operating systems: Linux (recommended), Solaris (deprecated), Unix (deprecated), Ubuntu (experimental), Windows (experimental), OS X (experimental)
Java Runtime Environment: Version 8 or higher
Database: PostgreSQL (recommended) or Oracle
Web server: Apache Tomcat (recommended) or Jetty
Browser: Chrome (recommended), Firefox (recommended), Safari (supported), Internet Explorer (supported)
Disk space: At least 10 GB
Memory: At least 4 GB
You can find more detailed information about the system requirements on the DSpace website.
To download DSpace 2017b, you need to visit the official website of DSpace at . There you can find the download links for different versions of DSpace. You can also access the release notes, documentation, support forums, newsletters, demos, etc.
DSpace 2017b is delivered on two files: the source code and the binary. The source code is for developers who want to customize or extend DSpace functionality. The binary is for users who want to install and run DSpace without modifying the code.
You can choose the file that suits your needs and download it to your system. The file size is about 200 MB for the source code and 100 MB for the binary. The file format is ZIP or TAR.GZ. You can use any software that can extract these files, such as WinZip, 7-Zip, or WinRAR.
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After you download the file, you need to extract it to a folder on your system. You can name the folder as you like, but we will use "dspace-2017b" as an example. You should see a folder structure like this:
dspace-2017b bin config dspace dspace-api dspace-jspui dspace-oai dspace-rest dspace-solr dspace-spring-rest dspace-xmlui etc lib webapps
The next step is to install DSpace 2017b on your system. The installation process may vary depending on your operating system and your preferences. Here are some general steps that you need to follow:
Create a database for DSpace using PostgreSQL or Oracle.
Create a user account for DSpace with appropriate permissions and roles.
Edit the configuration files in the "config" folder to suit your needs and preferences.
Run the installation script in the "bin" folder to build and deploy DSpace.
Start the web server and the DSpace services.
Verify that DSpace is running properly by accessing the web interface or the command line interface.
You can find more detailed instructions and examples for each step on the DSpace website.
How to Use DSpace 2017b with MATLAB
After you install DSpace 2017b, you can start using it with MATLAB to create, run, and test models using different tools and platforms. Here are some of the main steps that you need to follow:
Configure DSpace and MATLAB for integration and communication.
Create models using MATLAB and Simulink tools, such as Stateflow, RTI Blocksets, Real-Time Testing, TargetLink, VEOS, etc.
Run and test models using MATLAB and Simulink tools, such as Simulink Desktop Real-Time, Simulink Coder, Simulink Test, Simulink Coverage, etc.
Deploy models to hardware platforms using MATLAB and Simulink tools, such as Embedded Coder, Simulink Real-Time, Simulink PLC Coder, etc.
We will explain each step in more detail below.
Configure DSpace and MATLAB for integration and communication
To use DSpace and MATLAB together, you need to make sure that they can communicate with each other properly. This means that you need to configure some settings and parameters in both software packages. Here are some of the main things that you need to do:
Set up the network connection between your system and the hardware platform that you want to use with DSpace.
Install the required drivers and libraries for the hardware platform on your system.
Add the DSpace installation folder to the MATLAB path.
Select the appropriate compiler and linker options for MATLAB code generation.
Specify the target platform and communication protocol for MATLAB code deployment.
You can find more detailed information about how to configure DSpace and MATLAB on their websites.
Create models using MATLAB and Simulink tools
Once you have configured DSpace and MATLAB for integration and communication, you can start creating models using MATLAB and Simulink tools. MATLAB and Simulink provide a variety of tools and methods for modeling different systems and applications, such as engineering, science, education, finance, robotics, image processing, machine learning, and more.
Some of the main tools and methods that you can use with DSpace and MATLAB are:
Stateflow: A graphical tool for designing and simulating state machines and logic-driven systems. You can use Stateflow to model reactive systems, such as control systems, user interfaces, protocols, etc.
RTI Blocksets: A set of Simulink blocks that enable communication and data exchange between Simulink models and DSpace hardware platforms. You can use RTI Blocksets to configure the target platform, monitor signals, tune parameters, etc.
Real-Time Testing: A tool for testing and validating Simulink models in real time using DSpace hardware platforms. You can use Real-Time Testing to create test cases, execute tests, analyze results, generate reports, etc.
TargetLink: A tool for generating production-quality code from Simulink models. You can use TargetLink to generate C code or AUTOSAR code for DSpace hardware platforms or other embedded systems.
VEOS: A tool for virtual validation of software components on a PC. You can use VEOS to simulate the behavior of DSpace hardware platforms or other embedded systems without the need for physical hardware.
You can find more information about how to use these tools and methods on their websites.
Run and test models using MATLAB and Simulink tools
After you create models using MATLAB and Simulink tools, you can run and test them using different tools and methods. Running and testing models can help you verify their functionality, performance, robustness, and compliance with requirements and standards.
Some of the main tools and methods that you can use with DSpace and MATLAB are:
Simulink Desktop Real-Time: A tool for running Simulink models in real time on your PC. You can use Simulink Desktop Real-Time to simulate the behavior of DSpace hardware platforms or other embedded systems without the need for physical hardware.
Simulink Coder: A tool for generating executable code from Simulink models. You can use Simulink Coder to generate C code or MEX code for DSpace hardware platforms or other embedded systems.
Simulink Test: A tool for creating, managing, and executing test cases for Simulink models. You can use Simulink Test to automate testing workflows, compare results, generate reports, etc.
Simulink Coverage: A tool for measuring and analyzing the coverage of Simulink models during testing. You can use Simulink Coverage to identify untested or poorly tested parts of your models, improve test quality, generate reports, etc.
You can find more information about how to use these tools and methods on their websites.
Deploy models to hardware platforms using MATLAB and Simulink tools
The final step is to deploy your models to hardware platforms using MATLAB and Simulink tools. Deploying models to hardware platforms can help you implement your designs in real-world scenarios, such as prototyping, testing, production, etc.
Some of the main tools and methods that you can use with DSpace and MATLAB are:
Embedded Coder: A tool for generating optimized code from Simulink models for embedded systems. You can use Embedded Coder to generate C code or AUTOSAR code for DSpace hardware platforms or other embedded systems.
Simulink Real-Time: A tool for running Simulink models in real time on dedicated hardware platforms. You can use Simulink Real-Time to deploy your models to DSpace hardware platforms or other embedded systems.
Simulink PLC Coder: A tool for generating structured text code from Simulink models for programmable logic controllers (PLCs). You can use Simulink PLC Coder to generate IEC 61131-3 code or PLCopen XML code for DSpace hardware platforms or other PLCs.
You can find more information about how to use these tools and methods on their websites.
Conclusion
In this article, we have shown you how to download and use DSpace 2017b with MATLAB. We have covered the following topics:
What is DSpace and what is it used for?
What is MATLAB and what is it used for?
What are the benefits of using DSpace with MATLAB?
How to download DSpace 2017b and install it on your system.
How to configure DSpace and MATLAB for integration and communication.
How to create, run, and test models using DSpace and MATLAB tools.
How to deploy models to hardware platforms using DSpace and MATLAB tools.
We hope that this article has helped you understand how to use DSpace 2017b with MATLAB. DSpace and MATLAB are powerful software packages that can help you create, share, and reuse models and data in a secure and reliable way. They can also help you develop, test, and deploy models using various tools and methods, such as Simulink, Stateflow, RTI Blocksets, Real-Time Testing, TargetLink, VEOS, etc.
If you want to learn more about DSpace and MATLAB, you can visit their websites and access their documentation, tutorials, support forums, newsletters, demos, etc. You can also join their communities and contribute to their development.
If you have any feedback or questions about this article, please feel free to leave a comment below. We would love to hear from you and help you with any issues or doubts that you may have. Thank you for reading this article and happy modeling!
FAQs
What are the new features and enhancements in DSpace 2017b?
DSpace 2017b is the latest version of the software released in January 2018. It includes many new features and enhancements, such as:
A new REST API based on Spring Boot that provides a modern and flexible way to interact with DSpace.
A new Angular UI based on Angular 5 that provides a responsive and user-friendly web interface for DSpace.
A new submission process based on JSON Schema that allows users to customize the metadata fields and workflows for different collections.
A new authority control framework that allows users to link metadata values to external sources, such as ORCID, VIAF, etc.
A new statistics engine based on Solr that provides more accurate and comprehensive reports on usage and impact of DSpace content.
A new batch import/export tool based on CSV that allows users to migrate data between different versions or instances of DSpace.
A new command line interface that provides a consistent and easy way to perform administrative tasks on DSpace.
A new configuration system based on Apache Commons Configuration that allows users to manage settings in a hierarchical and modular way.
A new documentation system based on MkDocs that provides a clear and searchable documentation for DSpace.
How to update or upgrade from previous versions of DSpace?
If you are using a previous version of DSpace, such as 2016a or 2016b, you can update or upgrade to DSpace 2017b by following these steps:
Backup your existing data and configuration files.
Download the latest version of DSpace from the official website.
Extract the files to a folder on your system.
Run the update script in the "bin" folder to migrate your data and configuration files to the new version.
Run the installation script in the "bin" folder to build and deploy the new version of DSpace.
Start the web server and the DSpace services.
Verify that the update or upgrade was successful by accessing the web interface or the command line interface.
How to troubleshoot common issues or errors with DSpace 2017b?
If you encounter any issues or errors with DSpace 2017b, you can try these steps to troubleshoot them:
Check the log files in the "log" folder for any messages or exceptions that may indicate the cause of the problem.
Check the configuration files in the "config" folder for any errors or inconsistencies that may affect the behavior of DSpace.
Check the database tables for any corruption or inconsistency that may affect the data integrity of DSpace.
Check the web server settings and logs for any errors or warnings that may affect the performance or security of DSpace.
Check the network connection and firewall settings for any issues or restrictions that may prevent DSpace from communicating with other systems or services.
Check the documentation and support forums for any solutions or suggestions that may help you resolve the problem.
Contact the DSpace developers or community for any assistance or feedback that may help you fix the problem.
How to access documentation and support for DSpace 2017b?
If you need any documentation or support for DSpace 2017b, you can access them from various sources, such as:
The official website of DSpace at . There you can find the download links, release notes, documentation, support forums, newsletters, demos, etc.
The GitHub repository of DSpace at . There you can find the source code, issues, pull requests, wiki, etc.
The mailing lists of DSpace at . There you can subscribe to different lists, such as dspace-tech, dspace-devel, dspace-announce, etc.
The Slack channel of DSpace at . There you can chat with other DSpace users and developers in real time.
The IRC channel of DSpace at . There you can join the online chat room and talk with other DSpace users and developers.
How to join the DSpace community and contribute to its development?
If you want to join the DSpace community and contribute to its development, you can do so in various ways, such as:
Using DSpace and providing feedback and suggestions for improvement.
Reporting bugs and issues and proposing solutions or patches.
Developing new features and enhancements and submitting pull requests.
Writing documentation and tutorials and sharing them with others.
Providing support and assistance to other DSpace users and developers.
Promoting and advocating for DSpace in your institution or organization.
Donating or sponsoring DSpace development or events.
You can find more information about how to join the DSpace community and contribute to its development on their website. 44f88ac181
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